1. Field
The present disclosure relates generally to improved data manipulation techniques and, in particular, to a system and method for reducing irrelevant information generated during search activities by filtering out irrelevant results based on association of a data object's values to values of contexts associated with the data object.
2. Background
Parties searching for specific information, particularly during ongoing events when real time information is readily available and abundant, may be inundated with input from a plurality of sources. However, much of the input may have no relevance or value at the moment given the immediate and concentrated nature of the task or mission. Additionally, recent years have seen an exponential growth in the quantity and diversity of readily available information sources. Information sources have proliferated in quantity, depth and diversity because of linkage of databases using evolving technologies such as data tags and data mining. While these developments may be beneficial in many respects, the increased availability of real time information may cause difficulty for parties operating under time constraints and seeking actionable and timely information needed to complete a specific task. Such difficulty may be more pronounced when the heavy volume of received input concerns events taking place concurrently, and a party faced with making decisions is relying primarily or solely on the incoming rush of information.
In addition to the expanding quantity of information stored in databases and in other storage locations such as cloud-based media, the sheer volume of real-time and near real-time information about ongoing events has also increased exponentially in recent years. Internet-based video and online social networking and microblogging services are examples of this widely accessible content. The growth of interactive and user-collaborative media associated with the advent of the Web 2.0 internet has spawned an explosion of content. Such content is easily and readily accessible at minimal or no cost from public sources. However, receiving and processing such available information may be burdensome due to the sheer volume of the information and raw format with which it is made available. Even a large organization with significant processing and storage capacity may be overwhelmed by the quantity of information available. Much of the information may not be relevant to the organization's immediate objective which may be to take action in a currently developing and dynamic situation.
Cross-correlation of information has historically been a manual process. However, incoming data may not be analyzed rapidly enough for timely action, and most such analyses are performed in isolation. Parties participating in or overseeing such events and charged with making decisions about allocating resources or moving personnel may benefit from tools that quickly discard information that is not immediately relevant. Filtering out irrelevant information may increase the agility and accuracy of decision making. Filtering out irrelevant information also may decrease complexity, present fewer and clearer choices, and reduce expense arising from direct management costs and wasted resources. Filtering out irrelevant information also may reduce opportunity costs associated with disregarding a good choice. Thus, effective new techniques for filtering out irrelevant information are considered desirable.